Information Society
Code: 107572Credits: 6
| Degree programme | Type | Course |
|---|---|---|
| Business and Information Technology | OP | 4 |
Contact lecturer
- Name :
- Jordi Tena Sanchez
- Email :
- jordi.tena@uab.cat
Group languages
You can consult this information at the end of the document.
Prerequisites
The course will be held according to the Sustainable Development Goals (SDGs) perspective.
Objectives
This course offers a sociological analysis of some of the most important trends in contemporary societies: technological innovation, globalization, the evolution of labor markets, and social inequalities. Special emphasis is placed on these phenomena in relation to the development of digital economies.
Learning outcomes
- CM26 (Comply with ethical, legal and intellectual property principles in relation to the processing of private information in the business field.) Comply with ethical, legal and intellectual property principles in relation to the processing of private information in the business field.
Contents
- Introduction.
- Major theories of the Information Society.
- D. Bell.
- M. Castells.
- A. Giddens.
- Neo-Marxist and critical theories.
- Postmodernity.
- Critiques and limitations.
- Explaining the Information Society: social mechanisms and explanation in the social sciences.
- Social action and decision-making in the digital society.
- Rationality, norms and emotions.
- Risk and uncertainty.
- Bounded rationality.
- Information asymmetries.
- Trust and reputation.
- Technological change, innovation, risk and uncertainty.
- Diffusion of innovations.
- Technological controversies: nuclear energy and recent developments in artificial intelligence.
- From individual interactions to collective phenomena.
- Individualism, holism and emergence.
- Game theory.
- Agent-based modelling.
- Social networks.
- Small worlds.
- Random networks, small-world networks and scale-free networks.
- M. Granovetter and the strength of weak ties.
7Collective action and coordination dilemmas.
- M. Olson.
- D. Heckathorn.
- Exit, Voice and Loyalty.
- Critical mass and threshold models.
8Information, social influence and diffusion.
- Social influence.
- Informational cascades.
- Rumours.
- Imitation.
- Network effects.
- Virality.
9Institutions and coordination in the digital society.
10 Inequalities in the Information Society.
- The digital divide.
- Inequalities in access.
- Inequalities in digital skills.
- Algorithms and inequality.
11New information ecosystems: information, disinformation and artificial intelligence.
- Bots.
- Fake news.
- Generative AI.
- Traditional media.
- Digital social networks.
- Echo chambers.
- Polarization.
Learning activities and methodology
| Title | Hours | ECTS | Learning outcomes |
|---|---|---|---|
| Theoretical Sessions | 33 | 1.32 | CM26 |
| Practical sessions | 20 | 0.8 | CM26 |
| Tutorials | 10.5 | 0.42 | CM26 |
| Individual work. Analysis and learning readings | 55 | 2.2 | CM26 |
| Preparation for the seminars | 31.5 | 1.26 | CM26 |
The teaching methodology combines theoretical sessions with class debates, on the one hand, and practical seminars, on the other.
The practical seminars will be a space for dialogue on the course material based on various resources available on the virtual campus: texts, case analyses, film forums, etc.
Assessment
Continuous assessment activities
| Title | Weight | Hours | ECTS | Learning outcomes |
|---|---|---|---|---|
| Reading quizzes | 20% | 0 | 0 | CM26 |
| Exams | 50% | 0 | 0 | CM26 |
| Seminars | 30% | 0 | 0 | CM26 |
Continuous Assessment
Continuous assessment consists of three components: two midterm examinations, reading quizzes based on the compulsory bibliography, and participation in practical seminars (which may include the submission of in-class assignments).
Students will be considered eligible for assessment provided that they have completed assessment activities accounting for at least two-thirds of the final course grade. Students who do not meet this threshold may be recorded as "Not Assessable."
Any student who copies or attempts to copy during an examination will receive a final grade of 0 (Fail) for the course and will forfeit the right to the resit assessment. Likewise, any student who submits coursework containing evidence of plagiarism or who is unable to justify the arguments presented in their work will receive a grade of 0 for that assignment and a formal warning. Repeated misconduct will result in a final course grade of 0 (Fail) and the loss of the right to the resit assessment.
Use of Artificial Intelligence
Restricted use: In this course, the use of Artificial Intelligence (AI) technologies is permitted exclusively for support tasks, such as bibliographic or information searches. Students must clearly identify any parts generated using AI tools, specify the tools employed, and include a critical reflection on how these tools influenced both the process and the final outcome of the assignment. Failure to disclose the use of AI in assessed work will be considered a breach of academic integrity and may result in a partial or full penalty for the assignment, as well as more severe disciplinary measures in serious cases.
Resit Assessment
Students who are eligible for assessment but do not pass the course through continuous assessment will be entitled to take the resit assessment. Resit assessments will follow the same format as the corresponding continuous assessment activities. Specifically, midterm examinations will be retaken through equivalent examinations, while reading quizzes will be replaced by equivalent reading quizzes, and so forth.
Students who pass the course through the resit assessment may obtain a maximum final grade of 5 (Pass).
Bibliography
The bibliography of required readings, and therefore evaluable content, will be compiled in a reading dossier accessible through the virtual campus.
Software
No specific computer program is used.
Course groups and languages
The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE
| Type of teaching | Group | Language | Semester | Shift |
|---|---|---|---|---|
| (TE) Theory | 20 | Catalan | first semester | morning-mixed |
| (PAUL) Classroom practices | 20 | Catalan | first semester | morning-mixed |